Kelp vs Urchins
Nick Toimieri
sys.date()
1 Triggers and settings
2 Import Data
Note: for Neah Bay in 2016
- There are not algae data for the South Area only, the North.
- There are are only two transects of invert data for the North. There are 5 transects in the South area.
3 By KELP SPECIES but summed across all urchins
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
3.1 Individual plot version
The following splits the facet into individual plots for better plotting and labeling.
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
## `geom_smooth()` using formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
## `geom_smooth()` using formula 'y ~ x'
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
3.2 Site x Year regressions for urchins vs kelp
##
## Call:
## lm(formula = Kelp ~ Urchins, data = nereo[nereo$site == "Tatoosh Island",
## ])
##
## Residuals:
## 1 2 3 4 5 6
## -0.7437 1.4177 0.1734 -0.4836 0.5685 -0.9324
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.6353 0.7420 2.204 0.0922 .
## Urchins 0.1829 0.4716 0.388 0.7179
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.002 on 4 degrees of freedom
## Multiple R-squared: 0.03625, Adjusted R-squared: -0.2047
## F-statistic: 0.1505 on 1 and 4 DF, p-value: 0.7179##
## Call:
## lm(formula = Kelp ~ Urchins, data = nereo[nereo$site == "Destruction Island",
## ])
##
## Residuals:
## 1 2 3 4 5 6
## 0.19192 -0.18969 0.69401 0.03978 0.11496 -0.85098
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.2009 0.2720 4.415 0.0116 *
## Urchins -0.6686 0.8131 -0.822 0.4571
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5686 on 4 degrees of freedom
## Multiple R-squared: 0.1446, Adjusted R-squared: -0.06928
## F-statistic: 0.676 on 1 and 4 DF, p-value: 0.4571##
## Call:
## lm(formula = Kelp ~ Urchins, data = ptery[ptery$site == "Tatoosh Island",
## ])
##
## Residuals:
## 1 2 3 4 5 6
## 0.3096 -0.1753 -0.5812 0.4125 0.1880 -0.1535
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3932 0.3082 1.276 0.2710
## Urchins 0.8397 0.1959 4.287 0.0128 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4163 on 4 degrees of freedom
## Multiple R-squared: 0.8213, Adjusted R-squared: 0.7766
## F-statistic: 18.38 on 1 and 4 DF, p-value: 0.01278##
## Call:
## lm(formula = Kelp ~ Urchins, data = ptery[ptery$site == "Destruction Island",
## ])
##
## Residuals:
## 1 2 3 4 5 6
## -0.26042 0.23555 -0.12673 -0.03875 -0.02777 0.21811
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4795 0.1040 4.609 0.00997 **
## Urchins -0.1241 0.3110 -0.399 0.71026
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2175 on 4 degrees of freedom
## Multiple R-squared: 0.03828, Adjusted R-squared: -0.2021
## F-statistic: 0.1592 on 1 and 4 DF, p-value: 0.71034 Total for each.
I know we’re not supposed to combine macro & nereo but…just to see
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'site'. You can override using the
## `.groups` argument.
5 BY SPECIES
5.1 Transect level, all depths
##
## Attaching package: 'cowplot'## The following object is masked from 'package:ggpubr':
##
## get_legend## Loading required package: viridisLite
## By Site and Depth level
## `summarise()` has grouped output by 'year', 'site', 'zone'. You can override
## using the `.groups` argument.
## `summarise()` has grouped output by 'year', 'site', 'zone'. You can override
## using the `.groups` argument.## [1] 660 7## [1] 220 5## [1] 165 5
correlation purple vs nereo at Tatoosh r = 0.2273737, p = 0.0950256
5.2 By Site and 5 m only
## `summarise()` has grouped output by 'year', 'site', 'zone'. You can override
## using the `.groups` argument.
## `summarise()` has grouped output by 'year', 'site', 'zone'. You can override
## using the `.groups` argument.## [1] 660 7## [1] 220 5## [1] 165 5## $x
## [1] "Urchin density"
##
## $y
## [1] "Kelp density"
##
## $colour
## [1] "Site"
##
## attr(,"class")
## [1] "labels"
5.3 By site, averaged across depths, data = years
## `summarise()` has grouped output by 'year', 'site'. You can override using the
## `.groups` argument.
## `summarise()` has grouped output by 'year', 'site'. You can override using the
## `.groups` argument.## [1] 360 7## [1] 120 4## [1] 90 4
## [1] NA## [1] NAThis plot compared to the previous is interesting.
At the transect level, there is a negative correlation between urchin density and kelp neroycystis density at Tatoosh
At the site level, there is a positive correlation for Nerocystis (r = NA) and for Pterogophora (r = NA)at Tatoosh across years.
6 TATOOSH
6.1 By transect
##
## Formula: Y ~ a * exp(k * X)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## a 2.66810 0.51870 5.144 3.84e-06 ***
## k -0.11738 0.07926 -1.481 0.144
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.17 on 54 degrees of freedom
##
## Number of iterations to convergence: 8
## Achieved convergence tolerance: 8.24e-06## a k
## 2.6681018 -0.1173773## [1] 249.6557
7 Across years
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
8 Coastwide urchin - kelp patterns
8.1 All kelp: Nereo + Macro + Ptero
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
cor: r = 0.6822749; p = 0.1353868
8.2 Canopy only
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
cor r = 0.504957
8.3 Nero only
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
8.4 Macro only
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
## Ptero only
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
cor r = 0.8828724; = 0.0197749
9 Tatoosh only
## `summarise()` has grouped output by 'site', 'year', 'transect', 'area'. You can
## override using the `.groups` argument.##
## Formula: Y ~ a * exp(k * X)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## a 1.39499 0.21158 6.593 1.88e-08 ***
## k -0.12380 0.09697 -1.277 0.207
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9912 on 54 degrees of freedom
##
## Number of iterations to convergence: 5
## Achieved convergence tolerance: 7.215e-06## a k
## 1.3949945 -0.1237966## [1] 161.8996
## `summarise()` has grouped output by 'site', 'year', 'transect', 'area'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year', 'transect', 'area'. You can
## override using the `.groups` argument.##
## Formula: Y ~ a * exp(k * X)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## a 1.59528 0.34530 4.620 2.42e-05 ***
## k 0.01355 0.09324 0.145 0.885
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.909 on 54 degrees of freedom
##
## Number of iterations to convergence: 3
## Achieved convergence tolerance: 2.647e-06## a k
## 1.59527908 0.01354575## [1] 235.3155
## `summarise()` has grouped output by 'site', 'year', 'transect', 'area'. You can
## override using the `.groups` argument.##
## Formula: Y ~ a * exp(k * X)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## a 1.29906 0.28222 4.603 2.57e-05 ***
## k -0.08242 0.12451 -0.662 0.511
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.387 on 54 degrees of freedom
##
## Number of iterations to convergence: 16
## Achieved convergence tolerance: 7.605e-06## a k
## 1.29906302 -0.08242082## [1] 199.4928
10 Combined Figure 5
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
## `geom_smooth()` using formula 'y ~ x'
## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.
## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.
## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.
## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.
## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.##
## Attaching package: 'gridExtra'## The following object is masked from 'package:dplyr':
##
## combine## `geom_smooth()` using formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'
11 Kelp vs Kelp
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
Correlations between kelps
Macro vs Nereocystis, all sites r = -0.4863198 with p = 0.0064318
Macro vs Nereocystis, two sites r = 0.2257643 with p = 0.4804755
Macro vs Pterygophora, all sites r = 0.2289692 with p = 0.2235754
Macro vs Nereocystis, all sites r = 0.1389036 with p = 0.464145
12 Correlations at Tatoosh Island across years (yearly means) for different depth zones
A different, and simplified version of the above for just tatoosh and faceted by species.
Essentially, there are different relationships at different depths. Probably too much detail for this manuscript.
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year', 'zone'. You can override
## using the `.groups` argument.